基于PVAR模型的中国快速交通、旅游经济与旅游生态效率关系研究

doi:10.12118/j.issn.1000-6060.2024.789

Abstract

Abstract:

The coordinated interaction among rapid transportation, tourism economy, and tourism eco-efficiency is crucial for promoting the green transformation of tourism and achieving high-quality development. Based on China’s provincial panel data from 2009 to 2022, this study constructs a panel vector autoregression model to explore the interaction mechanisms, dynamic relationships, and regional heterogeneity among the three elements. The findings reveal that (1) Rapid transportation, tourism economy, and tourism eco-efficiency all exhibit positive growth trends, with a mainstream transition toward a benign equilibrium supported by gradual development from lower to higher levels. (2) Bidirectional Granger causality exists between rapid transportation and the tourism economy at both the national and eastern regional levels, implying a positive but short-lived interactive response. Rapid transportation has strong self-reinforcing characteristics, while the tourism economy is primarily self-driven yet significantly influenced by rapid transportation. (3) Only unidirectional Granger causality is observed between rapid transportation and tourism eco-efficiency. The positive driving effect of rapid transportation on tourism eco-efficiency tends to fluctuate and diminish, while the impact of tourism eco-efficiency on rapid transportation remains weak. Their interaction is notably imbalanced, with low mutual variance contribution rates. (4) Bidirectional Granger causality between the tourism economy and tourism eco-efficiency exists at the national level, characterized by strong and effective short-term driving of the tourism economy, which contrasts with the persistent weakness and disorderly effects of tourism eco-efficiency. Tourism eco-efficiency lacks sufficient endogenous momentum, with the tourism economy contributing the most to its variance in the eastern and central regions.

Key words: rapid transportation, tourism economy, tourism eco-efficiency, PVAR model

LI Yaru, BAI Yang, ZHOU Chunshan, CHEN Mingzhu. Relationship between rapid transportation, tourism economy and tourism eco-efficiency in China based on PVAR model[J].Arid Land Geography, 2026, 49(1): 106-116.

Figures/Tables 7

Fig. 1

Tab. 1

Tab. 2

Tab. 3

Tab. 4

Fig. 2

Tab. 5

References 35

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目标层	准则层	指标层	测算方法
快速交通	高速公路	路网密度/km∙km^-2	各省高速公路里程与国土面积之比
		路网衔接性/%	各省高速公路里程占公路总里程比例
		干线影响力/ 10⁴人∙d^-1	各省日均公路客运量
		通车覆盖率/%	各省高速公路通车地级市比例
	民航	通航密度/架次∙d^-1	各省日均飞机起降架次
		机场等级/分	依据各省境内机场飞行区等级，3C、4C、4D、4E、4F依次计2分、4分、6分、8分、10分，并求和
		通航覆盖率/%	各省民航通航地级市比例
		枢纽影响力/ 10⁴人∙d^-1	各省日均旅客吞吐量
	高铁	路网密度/km∙km^-2	各省高铁里程与国土面积之比
		站点密度/个∙km^-2	各省高铁站点数量与国土面积之比
		干线数量/条	各省高铁线路数量
		通车覆盖率/%	各省高铁通车地级市比例

变量	项目	HT	IPS	Fisher-ADF	检验结论
lnRTS	水平数据	-2.769^***	-5.604^***	195.473^***	平稳
lnTE		0.225	-1.971^**	48.999	不平稳
lnTEE		-3.209^***	-3.636^***	114.658^***	平稳
DlnRTS	一阶差分	-9.706^***	-9.576^***	286.120^***	平稳
DlnTE		-9.666^***	-6.744^***	142.364^***	平稳
DlnTEE		-13.090^***	-9.208^***	169.420^***	平稳

区域	滞后阶数	AIC	BIC	HQIC	区域	滞后阶数	AIC	BIC	HQIC
全国	1	9.260^*	-84.718^*	-28.606^*	中部	1	-18.771^*	-80.241^*	-43.243^*
	2	12.707	-49.944	-12.537		2	-13.546	-54.526	-29.860
	3	12.641	-18.648	0.019		3	-4.176	-24.666	-12.334
东部	1	-9.415^*	-78.653^*	-37.402^*	西部	1	-15.640	-77.110^*	-40.112^*
	2	-5.910	-52.069	-24.568		2	-16.282^*	-57.262	-32.596
	3	-4.144	-27.223	-13.473		3	-9.117	-29.607	-17.274

区域	变量	DlnRTS		DlnTE		DlnTEE
区域	变量	卡方	P值	卡方	P值	卡方	P值
全国	DlnRTS	-	-	3.262^*	0.071	4.748^**	0.029
	DlnTE	2.758^*	0.097	-	-	6.140^**	0.013
	DlnTEE	2.499	0.114	4.888^**	0.027	-	-
东部	DlnRTS	-	-	4.314^**	0.038	0.092	0.762
	DlnTE	3.126^*	0.077	-	-	1.287	0.257
	DlnTEE	0.559	0.455	1.768	0.184	-	-
中部	DlnRTS	-	-	0.879	0.349	0.137	0.712
	DlnTE	1.054	0.305	-	-	2.976^*	0.085
	DlnTEE	2.940^*	0.086	1.204	0.273	-	-
西部	DlnRTS	-	-	2.978^*	0.084	4.520^**	0.033
	DlnTE	0.003	0.954	-	-	3.038^*	0.081
	DlnTEE	2.057	0.152	0.441	0.507	-	-

预测期	响应变量		冲击变量				冲击变量
预测期	响应变量		DlnRTS	DlnTE	DlnTEE		DlnRTS	DlnTE	DlnTEE
1	DlnRTS	全国	1.000	0.000	0.000	中部	1.000	0.000	0.000
5			0.999	0.001	0.000		0.997	0.001	0.002
10			0.999	0.001	0.000		0.997	0.001	0.002
1	DlnTE		0.048	0.952	0.000		0.047	0.953	0.000
5			0.075	0.925	0.000		0.110	0.888	0.002
10			0.075	0.925	0.000		0.110	0.888	0.002
1	DlnTEE		0.022	0.502	0.477		0.013	0.560	0.427
5			0.023	0.479	0.498		0.017	0.536	0.447
10			0.023	0.479	0.498		0.017	0.536	0.447
1	DlnRTS	东部	1.000	0.000	0.000	西部	1.000	0.000	0.000
5			0.994	0.001	0.005		0.995	0.002	0.003
10			0.994	0.001	0.005		0.995	0.002	0.003
1	DlnTE		0.071	0.929	0.000		0.037	0.963	0.000
5			0.066	0.879	0.055		0.079	0.908	0.012
10			0.066	0.878	0.056		0.079	0.908	0.012
1	DlnTEE		0.028	0.616	0.356		0.027	0.396	0.577
5			0.029	0.618	0.353		0.047	0.363	0.590
10			0.029	0.618	0.353		0.047	0.363	0.590

Relationship between rapid transportation, tourism economy and tourism eco-efficiency in China based on PVAR model

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